/**
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You under the Apache License, Version 2.0
* (the "License"); you may not use this file except in compliance with
* the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.mahout.classifier.sequencelearning.hmm;
import org.apache.mahout.math.Matrix;
import org.junit.Test;
public class HMMEvaluatorTest extends HMMTestBase {
/**
* Test to make sure the computed model likelihood ist valid. Included tests
* are: a) forwad == backward likelihood b) model likelihood for test seqeunce
* is the expected one from R reference
*/
@Test
public void testModelLikelihood() {
// compute alpha and beta values
Matrix alpha = HmmAlgorithms.forwardAlgorithm(getModel(), getSequence(), false);
Matrix beta = HmmAlgorithms.backwardAlgorithm(getModel(), getSequence(), false);
// now test whether forward == backward likelihood
double forwardLikelihood = HmmEvaluator.modelLikelihood(alpha, false);
double backwardLikelihood = HmmEvaluator.modelLikelihood(getModel(), getSequence(),
beta, false);
assertEquals(forwardLikelihood, backwardLikelihood, EPSILON);
// also make sure that the likelihood matches the expected one
assertEquals(1.8425e-4, forwardLikelihood, EPSILON);
}
/**
* Test to make sure the computed model likelihood ist valid. Included tests
* are: a) forwad == backward likelihood b) model likelihood for test seqeunce
* is the expected one from R reference
*/
@Test
public void testScaledModelLikelihood() {
// compute alpha and beta values
Matrix alpha = HmmAlgorithms.forwardAlgorithm(getModel(), getSequence(), true);
Matrix beta = HmmAlgorithms.backwardAlgorithm(getModel(), getSequence(), true);
// now test whether forward == backward likelihood
double forwardLikelihood = HmmEvaluator.modelLikelihood(alpha, true);
double backwardLikelihood = HmmEvaluator.modelLikelihood(getModel(), getSequence(),
beta, true);
assertEquals(forwardLikelihood, backwardLikelihood, EPSILON);
// also make sure that the likelihood matches the expected one
assertEquals(1.8425e-4, forwardLikelihood, EPSILON);
}
}